3 papers
cs.CV2026
Characterizing Text Branch Sensitivity in Medical Vision-Language Segmentation via Evidence Decoupling
Ziquan Liu, Zhewei Zhu, Xuyang Shi
Pretrained vision-language models (VLMs) have shown promising performance in medical image segmentation by incorporating clinical text. However, it remains unclear how much textual…
cs.CV2026
InstEditSeg: Instruction-Driven Image Editing for Polyp and Skin Lesion Segmentation
Ziquan Liu, Zhewei Zhu, Xuyang Shi
Accurate segmentation of polyps and skin lesions is pivotal for clinical diagnosis, yet existing methods struggle with low contrast, ambiguous boundaries, and cross-domain distribu…
cs.CV2026
FAN-LoRA: A Fourier-Adaptive Nonlinear Low-Rank Adaptor for Medical Foundation Model Domain Adaptation
Ziquan Liu, Zhewei Zhu, Xuyang Shi
The advent of vision foundation models, notably the Segment Anything Model (SAM), has catalyzed significant advancements in natural image segmentation. However, their direct transf…